3 papers
cs.RO2026
DenseReward: Dense Reward Learning via Failure Synthesis for Robotic Manipulation
Yu Fang, Wanxi Dong, Jiaqi Liu +7
Reinforcement learning holds great promise for improving robot policies beyond the limits of imitation learning. However, its practical adoption remains bottlenecked by the lack of…
cs.RO2026
R3DP: Real-Time 3D-Aware Policy for Embodied Manipulation
Yuhao Zhang, Wanxi Dong, Yue Shi +13
Embodied manipulation requires accurate 3D understanding of objects and their spatial relations to plan and execute contact-rich actions. While large-scale 3D vision models provide…
cs.RO2025
HyCodePolicy: Hybrid Language Controllers for Multimodal Monitoring and Decision in Embodied Agents
Yibin Liu, Zhixuan Liang, Zanxin Chen +7
Recent advances in multimodal large language models (MLLMs) have enabled richer perceptual grounding for code policy generation in embodied agents. However, most existing systems l…